4/5/2023 0 Comments Colorcompass![]() ![]() ![]() It includes the connection and initialization of the sensor, the control of the exposure time, the display of the image in real time, the acquisition and storage, and the calculation of the reflectance. The software part was written using the Qt library and the C++ programming language. The hardware part of the device includes a spectral camera based on a snapshot-mosaic sensor, a main control unit, a network module, a storage module, a power supply module, and a display and remote-control device. To achieve rapid nondestructive detection of chlorophyll content in crops in a field environment, we designed a new lightweight device based on a snapshot-mosaic imaging sensor given the sensitive properties of chlorophyll in the red-edge to near-infrared band (700–900 nm) and the advantages of imaging spectroscopy in environmental noise separation. The coefficients of determination of the regression models based on 1D-CNN were almost same (with R2 = 0.94) and the ratios of performance to deviation based on reflectance after spectral correction using a second-degree polynomial for the Colorcompass-LF and the FieldSpec4 were 4.31 and 4.33, respectively The results from an independent validation dataset confirmed the good performance of the Colorcompass-LF after spectral correction using a second-degree polynomial, and very similar estimation accuracies were obtained for the measurements from the FieldSpec4. ![]() The chlorophyll content was estimated using regression models based on a one-dimensional convolutional neural network (1D-CNN) that was generated after the original reflectance from the spectrometer measurements was de-noised. The chlorophyll contents per leaf area (cm2) of radish were generally higher than those of wasabi and ranged from 42.20 to 94.39 μg/cm2 and 11.39 to 40.40 μg/cm2 for radish and wasabi, respectively. In this study, a system based on a cost-effective fingertip-sized spectrometer (Colorcompass-LF, a total price for the proposed solution was approximately 1600 USD) was evaluated for its ability to estimate the chlorophyll contents of radish and wasabi leaves and was compared with the Analytical Spectral Devices FieldSpec4. However, the prices of these devices have not yet decreased to consumer-affordable levels, which prevents widespread use. Hyperspectral reflectance has been used to evaluate vegetation properties such as pigment content, plant structure and physiological features using portable spectroradiometers. Leaf chlorophyll content is used as a major indicator of plant stress and growth, and hyperspectral remote sensing is frequently used to monitor the chlorophyll content. ![]()
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